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adaptive quadrature algorithm  (STATA Corporation)


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    STATA Corporation adaptive quadrature algorithm
    Adaptive Quadrature Algorithm, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 33928 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/adaptive+quadrature+algorithm/STATA+13%2E0/pm27273127-108-6-15
    Average 99 stars, based on 33928 article reviews
    adaptive quadrature algorithm - by Bioz Stars, 2026-10
    99/100 stars

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    other:

    Article Title: The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital
    Article Snippet: Univariable multilevel Poisson models were fit using marginal likelihood estimation via the adaptive quadrature algorithm (as implemented in the xtmepoisson procedure in Stata) to screen each independent variable with the dependent variable using a liberal significance level (α ≤ 0.20).

    Article Title: Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006–2011
    Article Snippet: Univariable multilevel Poisson models were fit using marginal likelihood estimation via the adaptive quadrature algorithm (as implemented in the xtmepoisson procedure in Stata) to screen each independent variable with the dependent variable using a liberal significance level (α ≤ 0.20).

    Software:

    Article Title: Correlated versus uncorrelated frailty Cox models: A comparison of different estimation procedures.
    Article Snippet: In many studies in medicine, including clinical trials and epidemiological investigations, data are clustered into groups such as health centers or herds in veterinary medicine.. Such data are usually analyzed by hierarchical regression models to account for possible variation between groups.. When such variation is large, it is of potential interest to explore whether additionally the effect of a within-group predictor varies between groups.



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